Solving navigation tasks with learned Teleo-Reactive Programs

Programming a robot to perform tasks in dynamic environments is a complex process. Teleo-reactive programs (TRPs) (S. Benson and N.J. Nilsson, 1995) have proved to be an effective framework to continuously perform a set of actions to achieve particular goals and react in the presence of unexpected events, however, their definition is a difficult and time-consuming process. In this paper, it is shown how a robot can learn TRPs from human guided traces. A user guides a robot to perform a task and the robot learns how to perform such task in similar dynamic environments.